Our platform guides you through a comprehensive DNA mutation analysis process, leveraging Stanford's Evo 2 AI to deliver accurate pathogenicity assessments.
Enter the gene of interest (e.g., BRCA1, TP53) in the search input. The system fetches associated data including gene structure, known variants, and transcript information.
Input the specific mutation or variant (e.g., c.68_69delAG or p.Glu23Ter). The system parses this using HGVS notation and validates your input.
Choose your analysis purpose: Pathogenicity Prediction, Disease Association, Population Frequency, or Research Comparison.
Our AI/ML pipeline is triggered to predict functional impact, check existing variant databases (ClinVar, dbSNP, gnomAD), and compare with known pathogenic/benign mutations.
View visual genome maps showing mutation location, protein structure impact (if applicable), and conservation across species.
Review results showing classification (Pathogenic/Likely Pathogenic/Benign/Likely Benign/VUS), prediction confidence (%), and supporting evidence from clinical studies.
Unlock groundbreaking insights with tools built to accelerate research and detect diseases early.
